Techniques for benchmarking performance in a contact center system

ABSTRACT

Techniques for benchmarking performance in a contact center system are disclosed. In one particular embodiment, the techniques may be realized as a method for benchmarking contact center system performance comprising cycling, by at least one computer processor configured to perform contact center operations, between a first contact-agent pairing strategy and a second contact-agent pairing strategy for pairing contacts with agents in the contact center system; determining an agent-utilization bias in the first contact-agent pairing strategy comprising a difference between a first agent utilization of the first contact-agent pairing strategy and a balanced agent utilization; and determining a relative performance of the second contact-agent pairing strategy compared to the first contact-agent pairing strategy based on the agent-utilization bias in the first contact-agent pairing strategy.

CROSS-REFERENCE TO RELATED APPLICATIONS

This patent application is a continuation of U.S. patent applicationSer. No. 17/093,076, filed on Nov. 19, 2020, which is a continuation ofU.S. patent application Ser. No. 16/198,419, filed on Nov. 21, 2018, nowU.S. Pat. No. 10,834,259, which is a continuation of U.S. patentapplication Ser. No. 15/176,899, filed Jun. 8, 2016, now U.S. Pat. No.10,142,473, each of which is hereby incorporated by reference herein inits entirety.

FIELD OF THE DISCLOSURE

This disclosure generally relates to contact centers and, moreparticularly, to techniques for benchmarking performance in a contactcenter system.

BACKGROUND OF THE DISCLOSURE

A typical contact center algorithmically assigns contacts arriving atthe contact center to agents available to handle those contacts. Attimes, the contact center may have agents available and waiting forassignment to inbound or outbound contacts (e.g., telephone calls,Internet chat sessions, email). At other times, the contact center mayhave contacts waiting in one or more queues for an agent to becomeavailable for assignment.

In some typical contact centers, contacts are assigned to agents orderedbased on the time when those agents became available, and agents areassigned to contacts ordered based on time of arrival. This strategy maybe referred to as a “first-in, first-out”, “FIFO”, or “round-robin”strategy.

Some contact centers may use a “performance based routing” or “PBR”approach to ordering the queue of available agents or, occasionally,contacts. PBR ordering strategies attempt to maximize the expectedoutcome of each contact-agent interaction but do so typically withoutregard for uniformly utilizing agents in a contact center.

When a contact center changes from using one type of pairing strategy(e.g., FIFO) to another type of pairing strategy (e.g., PBR), someagents may be available to receive a contact, while other agents may beon a call. If the average agent performance over time is unbalanced, theoverall performance of one type of pairing strategy may be unfairlyinfluenced by the other type of pairing strategy.

In view of the foregoing, it may be understood that there may be a needfor a system that enables benchmarking contact center system performanceincluding transition management of alternative routing strategies todetect and account for unbalanced average agent performance amongalternative pairing strategies.

SUMMARY OF THE DISCLOSURE

Techniques for benchmarking performance in a contact center system aredisclosed. In one particular embodiment, the techniques may be realizedas a method for benchmarking contact center system performancecomprising cycling, by at least one computer processor configured toperform contact center operations, between a first contact-agent pairingstrategy and a second contact-agent pairing strategy for pairingcontacts with agents in the contact center system, determining, by theat least one computer processor, an agent-utilization bias in the firstcontact-agent pairing strategy comprising a difference between a firstagent utilization of the first contact-agent pairing strategy and abalanced agent utilization, and determining, by the at least onecomputer processor, a relative performance of the second contact-agentpairing strategy compared to the first contact-agent pairing strategybased on the agent-utilization bias in the first contact-agent pairingstrategy.

In accordance with other aspects of this particular embodiment, themethod may further include adjusting, by the at least one computerprocessor, a target agent utilization of the second contact-agentpairing strategy to reduce the agent-utilization bias in the firstcontact-agent pairing strategy.

In accordance with other aspects of this particular embodiment, themethod may further include determining, by the at least one computerprocessor, an average available-agent performance of a plurality ofagents during at least one transition from the first contact-agentpairing strategy to the second contact-agent pairing strategy.

In accordance with other aspects of this particular embodiment, themethod may further include determining, by the at least one computerprocessor, an average availability of at least one of a plurality ofagents during at least one transition from the first contact-agentpairing strategy to the second contact-agent pairing strategy.

In accordance with other aspects of this particular embodiment, themethod may further include outputting, by the at least one computerprocessor, a transition management report comprising theagent-utilization bias of the first contact-agent pairing strategy.

In accordance with other aspects of this particular embodiment, thefirst contact-agent pairing strategy may be a performance-based routingstrategy.

In accordance with other aspects of this particular embodiment, thesecond contact-agent pairing strategy may be a behavioral pairingstrategy.

In accordance with other aspects of this particular embodiment, thesecond contact-agent pairing strategy may be a hybrid behavioral pairingstrategy, and the hybrid behavioral pairing strategy may be biasedtoward a performance-based routing strategy.

In accordance with other aspects of this particular embodiment, themethod may further include adjusting, by the at least one computerprocessor, at least one parameter of the second contact-agent pairingstrategy.

In accordance with other aspects of this particular embodiment, the atleast one parameter comprises a Kappa parameter for a hybrid behavioralpairing strategy.

In accordance with other aspects of this particular embodiment, thefirst contact-agent pairing strategy may target an unbalanced agentutilization, and the second contact-agent pairing strategy may targetthe balanced agent utilization.

In accordance with other aspects of this particular embodiment, thetarget utilization of the second contact-agent pairing strategy may beadjusted at least once at one or more points in time between atransition from the first to the second contact-agent pairing strategyand a subsequent transition from the second to the first contact-agentpairing strategy.

In another particular embodiment, the techniques may be realized as asystem for benchmarking performance in a contact center systemcomprising at least one processor, wherein the at least one processor isconfigured to perform the above-described method.

In another particular embodiment, the techniques may be realized as anarticle of manufacture for benchmarking performance in a contact centersystem comprising: a non-transitory processor readable medium; andinstructions stored on the medium; wherein the instructions areconfigured to be readable from the medium by at least one processor andthereby cause the at least one processor to operate so as to perform theabove-described method.

The present disclosure will now be described in more detail withreference to particular embodiments thereof as shown in the accompanyingdrawings. While the present disclosure is described below with referenceto particular embodiments, it should be understood that the presentdisclosure is not limited thereto. Those of ordinary skill in the arthaving access to the teachings herein will recognize additionalimplementations, modifications, and embodiments, as well as other fieldsof use, which are within the scope of the present disclosure asdescribed herein, and with respect to which the present disclosure maybe of significant utility.

BRIEF DESCRIPTION OF THE DRAWINGS

In order to facilitate a fuller understanding of the present disclosure,reference is now made to the accompanying drawings, in which likeelements are referenced with like numerals. These drawings should not beconstrued as limiting the present disclosure, but are intended to beillustrative only.

FIG. 1 shows a block diagram of a contact center system according toembodiments of the present disclosure.

FIG. 2 shows a schematic representation of an agent transition tableaccording to embodiments of the present disclosure.

FIG. 3 shows a schematic representation of an agent transition tableaccording to embodiments of the present disclosure.

FIG. 4 depicts a schematic representation of an agent transition chartaccording to embodiments of the present disclosure.

FIG. 5 depicts a schematic representation of an agent transition chartaccording to embodiments of the present disclosure.

FIG. 6 shows a schematic representation of an agent transition chartaccording to embodiments of the present disclosure.

FIG. 7 shows a schematic representation of an agent transition chartaccording to embodiments of the present disclosure.

FIG. 8 shows a flow diagram of a benchmarking transition managementmethod according to embodiments of the present disclosure.

DETAILED DESCRIPTION

A typical contact center algorithmically assigns contacts arriving atthe contact center to agents available to handle those contacts. Attimes, the contact center may have agents available and waiting forassignment to inbound or outbound contacts (e.g., telephone calls,Internet chat sessions, email). At other times, the contact center mayhave contacts waiting in one or more queues for an agent to becomeavailable for assignment.

In some typical contact centers, contacts are assigned to agents orderedbased on the time when those agents became available, and agents areassigned to contacts ordered based on time of arrival. This strategy maybe referred to as a “first-in, first-out”, “FIFO”, or “round-robin”strategy. For example, a longest-available agent pairing strategypreferably selects the available agent who has been available for thelongest time.

Some contact centers may use a “performance based routing” or “PBR”approach to ordering the queue of available agents or, occasionally,contacts. PBR ordering strategies attempt to maximize the expectedoutcome of each contact-agent interaction but do so typically withoutregard for uniformly utilizing agents in a contact center. Some variantsof PBR may include a highest-performing-agent pairing strategy,preferably selecting the available agent with the highest performance,or a highest-performing-agent-for-contact-type pairing strategy,preferably selecting the available agent with the highest performancefor the type of contact being paired.

For yet another example, some contact centers may use a “behavioralpairing” or “BP” strategy, under which contacts and agents may bedeliberately (preferentially) paired in a fashion that enables theassignment of subsequent contact-agent pairs such that when the benefitsof all the assignments under a BP strategy are totaled they may exceedthose of FIFO and PBR strategies. BP is designed to encourage balancedutilization of agents within a skill queue while neverthelesssimultaneously improving overall contact center performance beyond whatFIFO or PBR methods will allow. This is a remarkable achievementinasmuch as BP acts on the same calls and same agents as FIFO or PBRmethods, utilizes agents approximately evenly as FIFO provides, and yetimproves overall contact center performance. BP is described in, e.g.,U.S. Pat. No. 9,300,802, which is incorporated by reference herein.Additional information about these and other features regarding thepairing or matching modules (sometimes also referred to as “SATMAP”,“routing system”, “routing engine”, etc.) is described in, for example,U.S. Pat. No. 8,879,715, which is incorporated by reference herein.

In some embodiments, a contact center may switch (or “cycle”)periodically among at least two different pairing strategies (e.g.,between FIFO and PBR; between PBR and BP; among FIFO, PBR, and BP).Additionally, the outcome of each contact-agent interaction may berecorded along with an identification of which pairing strategy (e.g.,FIFO, PBR, or BP) had been used to assign that particular contact-agentpair. By tracking which interactions produced which results, the contactcenter may measure the performance attributable to a first strategy(e.g., FIFO) and the performance attributable to a second strategy(e.g., PBR). In this way, the relative performance of one strategy maybe benchmarked against the other. The contact center may, over manyperiods of switching between different pairing strategies, more reliablyattribute performance gain to one strategy or the other. Additionalinformation about these and other features regarding benchmarkingpairing strategies is described in, for example, U.S. patent applicationSer. No. 15/131,915, filed Apr. 20, 2016.

When a contact center changes from using one type of pairing strategy(e.g., PBR) to another type of pairing strategy (e.g., BP), some agentsmay be available to receive a contact, while other agents may beinteracting with a contact (e.g., on a call). If the average agentperformance at transitions over time is unbalanced, the overallperformance of one type of pairing strategy may be unfairly influencedby the other type of pairing strategy. For example, when a contactcenter pairs contacts and agents using PBR, high-performing agents aremore likely to be busy interacting with a contact, while low-performingagents are more likely to be idle. Thus, at transitions from PBR toanother pairing strategy such as BP, the average performance ofavailable agents at transitions over time is likely to be below theaverage performance of all of the agents including both the availableagents and the busy agents.

FIG. 1 shows a block diagram of a contact center system according toembodiments of the present disclosure. As shown in FIG. 1, the contactcenter system 100 may include a central switch 110. The central switch110 may receive incoming contacts (e.g., callers) or support outboundconnections to contacts via a telecommunications network (not shown).The central switch 110 may include contact routing hardware and softwarefor helping to route contacts among one or more contact centers, or toone or more PBX/ACDs or other queuing or switching components within acontact center.

The central switch 110 may not be necessary if there is only one contactcenter, or if there is only one PBX/ACD routing component, in thecontact center system 100. If more than one contact center is part ofthe contact center system 100, each contact center may include at leastone contact center switch (e.g., contact center switches 120A and 120B).The contact center switches 120A and 120B may be communicatively coupledto the central switch 110.

Each contact center switch for each contact center may becommunicatively coupled to a plurality (or “pool”) of agents. Eachcontact center switch may support a certain number of agents (or“seats”) to be logged in at one time. At any given time, a logged-inagent may be available and waiting to be connected to a contact, or thelogged-in agent may be unavailable for any of a number of reasons, suchas being connected to another contact, performing certain post-callfunctions such as logging information about the call, or taking a break.

In the example of FIG. 1, the central switch 110 routes contacts to oneof two contact centers via contact center switch 120A and contact centerswitch 120B, respectively. Each of the contact center switches 120A and120B are shown with two agents each. Agents 130A and 130B may be loggedinto contact center switch 120A, and agents 130C and 130D may be loggedinto contact center switch 120B.

The contact center system 100 may also be communicatively coupled to anintegrated service from, for example, a third party vendor. In theexample of FIG. 1, transition management module 140 may becommunicatively coupled to one or more switches in the switch system ofthe contact center system 100, such as central switch 110, contactcenter switch 120A, or contact center switch 120B. In some embodiments,switches of the contact center system 100 may be communicatively coupledto multiple benchmarking modules. In some embodiments, transitionmanagement module 140 may be embedded within a component of a contactcenter system (e.g., embedded in or otherwise integrated with a switch).The transition management module 140 may receive information from aswitch (e.g., contact center switch 120A) about agents logged into theswitch (e.g., agents 130A and 130B) and about incoming contacts viaanother switch (e.g., central switch 110) or, in some embodiments, froma network (e.g., the Internet or a telecommunications network) (notshown).

A contact center may include multiple pairing modules (e.g., a BP moduleand a FIFO module) (not shown), and one or more pairing modules may beprovided by one or more different vendors. In some embodiments, one ormore pairing modules may be components of transition management module140 or one or more switches such as central switch 110 or contact centerswitches 120A and 120B. In some embodiments, a transition managementmodule 140 may determine which pairing module may handle pairing for aparticular contact. For example, the transition management module 140may alternate between enabling pairing via the BP module and enablingpairing with the FIFO module. In other embodiments, one pairing module(e.g., the BP module) may be configured to emulate other pairingstrategies. For example, a transition management module 140, or atransition management component integrated with BP components in the BPmodule, may determine whether the BP module may use BP pairing oremulated FIFO pairing for a particular contact. In this case, “BP on”may refer to times when the BP module is applying the BP pairingstrategy, and “BP off” may refer to other times when the BP module isapplying a different pairing strategy (e.g., FIFO).

In some embodiments, regardless of whether pairing strategies arehandled by separate modules, or if some pairing strategies are emulatedwithin a single pairing module, the single pairing module may beconfigured to monitor and store information about pairings made underany or all pairing strategies. For example, a BP module may observe andrecord data about FIFO pairings made by a FIFO module, or the BP modulemay observe and record data about emulated FIFO pairings made by a BPmodule operating in FIFO emulation mode.

Embodiments of the present disclosure are not limited to benchmarkingtransition management of only two pairing strategies. Instead,benchmarking transition management may be performed for two or morepairing strategies (e.g., benchmarking transition management of FIFO,PBR, and BP).

FIG. 2 shows a schematic representation of an agent transition table 200according to embodiments of the present disclosure. In the example ofFIG. 2, four agents named “Alice”, “Bob”, “Charlie”, and “Donna” may beassigned to a particular queue for interacting with contacts. Theseagent names are for illustrative purposes only; in some embodiments,anonymized identification numbers or other identifiers may be used torepresent agents in a contact center. Additionally, this highlysimplified example only shows four agents. In some embodiments, hundredsof agents, thousands of agents, or more may be assigned to a queue andmay be depicted in an agent transition table.

Agent transition table 200 shows five transitions labeled “201”, “202”,“203”, “204”, and “205”. In some embodiments, each transition mayrepresent a point in time at which a contact center switches from onepairing strategy (e.g., FIFO) to another pairing strategy (e.g., BP).Transitions may occur multiple times per hour (e.g., every 10 minutes,every 15 minutes, every 30 minutes) or more or less frequentlythroughout a day, week, month, year, etc. In some embodiments,transitions may be identified by the time of day at which the transitionoccurred. For example, transition 201 may have occurred at time 9:15 AM,transition 202 may have occurred at time 9:45 AM, etc.

At transition 201, agents Alice and Bob are not available, as indicatedby shaded cells. For example, Alice and Bob may be interacting with acontact, or they may be otherwise occupied with a post-interaction tasksuch as logging a sale or filing a customer service report. Meanwhile,agents Charlie and Donna are idle or otherwise available to be connectedto a contact, as indicated by unshaded cells.

Similarly, at transition 202, agents Charlie and Donna are busy, andagents Alice and Bob are available. At transition 203, agents Alice andCharlie are busy, and agents Bob and Donna are available. At transition204, agents Bob and Donna are busy, and agents Alice and Charlie areavailable. At transition 205, agents Bob and Charlie are busy, andagents Alice and Donna are available.

At any single transition, even pairing strategies that target balancedagent utilization (e.g., FIFO and BP, but not PBR) may appear to haveskewed utilization at transitions. For example, if Alice has anormalized performance rating of 80, Bob a rating of 60, Charlie arating of 40, and Donna a rating of 20, the average performance of allagents is 50. However, the average performance of the available agentsat transition 201 (i.e., Charlie and Donna) is below average at 30. Theaverage performance of the available agents at transition 202 is aboveaverage at 70. The average performance of the available agents attransition 203 is below average at 40. The average performance of theavailable agents at transition 204 is above average at 60.

At some transitions, even pairing strategies that target unbalancedagent utilization (e.g., PBR) may appear to have balanced utilization attransitions. For example, at transition 205, the average performance ofthe available agents (i.e., Alice and Donna) is 50.

Despite variance in average performance of available agents at anysingle transition, the average performance of available agents atmultiple transitions over time (e.g., over the course of a day) mayreflect the statistically expected utilization of a given pairingstrategy. Agent transition table 200 shows five transitions 201-205,which, in some embodiments, may not be a statistically significantnumber of transitions. Nevertheless, for illustrative purposes, theaverage available agent performance over the course of the fivetransitions 201-205 is (30+70+40+60+50)/5=50. In this example, theaverage available agent performance at the transitions over the courseof five transitions 201-205 was balanced.

In some embodiments, in addition to or instead of determining theaverage performance of available agents over one or more transitions,the average availability of individual agents may also be determined andoutputted. For example, in agent transition table 200, the averageavailability of each agent over each transition 201-205 is 60% for Alice(3 of 5 transitions), 40% for Bob (2 of 5 transitions), 40% for Charlie(2 of 5 transitions), and 60% for Donna (4 of 5 transitions). Forpairing strategies that target balanced agent utilization (e.g., FIFO orBP), it may be statistically likely for each agent to be availableapproximately the same number of times or same proportion oftransitions. In this simplified example, which depicts only fivetransitions 201-205, the average availability of each agent variesbetween 40% and 60%. However, over time, the average availability ofeach agent may be statistically likely to converge to the samepercentage. For example, after 100 transitions, the average availabilityof every agent may approximately the same, e.g., 50%, 55%, 60%, etc.

FIG. 3 shows a schematic representation of an agent transition table 300according to embodiments of the present disclosure. In contrast to theexample of agent transition table 200 (FIG. 2), agent transition table300 shows outcomes that would typically be expected in a contact centerusing an unbalanced pairing strategy such as PBR. In some embodiments ofPBR, the highest-performing agent (i.e., Alice) may be preferablyselected to interact with contacts. Consequently, Alice is neveravailable at any of the transitions 301-305. Meanwhile, thelowest-performing agent (i.e., Donna) is always available at each of thetransitions 301-305.

The average performance of available agents is 30 at transition 301, 40at transition 302, 30 at transition 303, 20 at transition 304, and 40 attransition 305. The average performance of available agents over thecourse of five transitions 301-305 is unbalanced at(30+40+30+20+40)/5=32. The extent to which the average performance ofavailable agents over time may show a statistically significant amountof skew in agent utilization that could “pollute”, bias, or otherwiseinfluence the effectiveness of alternative pairing strategies followingeach transition, resulting in potentially unfair benchmarkingmeasurements.

In some embodiments, in addition to or instead of determining theaverage performance of available agents over one or more transitions,the average availability of individual agents may also be determined andoutputted. For example, in agent transition table 300, the averageavailability of each agent over each transition 301-305 is 0% for Alice(0 of 5 transitions), 40% for Bob (2 of 5 transitions), 60% for Charlie(3 of 5 transitions), and 100% for Donna (5 of 5 transitions). Forpairing strategies that target unbalanced agent utilization (e.g., PBR),it may be statistically likely for some agents (e.g., lower-performingagents) to be available significantly more often than other agents(e.g., higher-performing agents). Even in this simplified example, whichdepicts only five transitions 501-505, the average availability of eachagent varies significantly between 0% and 100%. Over time, thestatistical significance of the varying average availability of eachagent may be further confirmed. Here, an unbalanced pairing strategysuch as PBR always or almost always hands off lower-performing agents tothe next pairing strategy (e.g., BP or FIFO), while thehigher-performing agents are never or almost never handed off. Asexplained above in reference to average agent quality at one or moretransitions, the extent to which the average availability of agents overtime may show a statistically significant amount of skew in agentutilization that could “pollute”, bias, or otherwise influence theeffectiveness of alternative pairing strategies following eachtransition, resulting in potentially unfair benchmarking measurements.

FIG. 4 depicts a schematic representation of an agent transition chart400 according to embodiments of the present disclosure. In agenttransition chart 400, the x-axis indicates a period of time. Forexample, x=0 may represent a first day, x=1 a second day, etc. over thecourse of a week. The y-axis indicates the average performance ofavailable agents over all of the transitions from a first pairingstrategy to a second pairing strategy during a given time period. Forexample, at x=0 (e.g., Day 1), the average performance of availableagents at transitions over the course of the day was 50. At x=1 (e.g.,Day 2), the average performance was slightly above average, and at x=3(e.g., Day 4), the average performance was slightly below average.Nevertheless, the agent transition chart 400 shows a relatively steadyaverage performance over relatively longer time periods (e.g., a week).In some embodiments, the small amount of variability from day to day maybe statistically insignificant, and the overall agent utilization forthis first pairing strategy is balanced.

FIG. 5 depicts a schematic representation of an agent transition chart500 according to embodiments of the present disclosure. In agenttransition chart 500, the overall agent utilization remains steady atabout 25 from day to day, which is significantly below average. Thus,the overall agent utilization for this pairing strategy (e.g., PBR) isunbalanced.

When benchmarking among multiple pairing strategies, it is possible fora first pairing strategy (e.g., PBR) to “pollute” or otherwise bias theperformance of a second pairing strategy (e.g., FIFO or BP). At eachtransition from PBR to BP, the average performance of available agentsmay be significantly below the overall average performance of all agentsassigned to the queue (i.e., unbalanced). This “suppressed” agent poolat the beginning of a BP or FIFO cycle may weaken the overallperformance of BP or FIFO for that cycle.

Conversely, at each transition from BP or FIFO to PBR, the averageperformance of available agents may be similar or equal to the overallaverage performance of all agents assigned to the queue (i.e.,balanced). This balanced agent pool at the beginning of each PBR cyclemay enhance the overall performance of PBR for that cycle, because evena balanced agent pool may be better than the typical agent pool that PBRcauses.

Because each PBR cycle may leave the agent pool more “polluted”(unbalanced) than when it received it, and each BP or FIFO cycle mayleave the agent pool “cleaner” (balanced) than when it received it, sometechniques for benchmarking PBR against BP or FIFO may give theappearance that BP or FIFO are performing worse than they otherwisewould be if the PBR cycles were not polluting their available agentpools at the beginning of each cycle. Thus, it may be helpful to comparethe average performance of available agents at the beginning (“fronthalf”) of a cycle with the average performance of available agents atthe end (“back half”) of the cycle.

FIG. 6 shows a schematic representation of an agent transition chart 600according to embodiments of the present disclosure. Agent transitionchart 600 shows an example front-half/back-half comparison. At x=0(e.g., Day 1), the difference between the average performance ofavailable agents transitioning into a first pairing strategy and out ofthe first pairing strategy over the course of the day was 0. At x=1, thedifference was slightly above 0, and at x=3 the difference was slightlybelow 0, but the overall differences over the course of a week stayedclose to 0. Conceptually, the pairing strategies were leaving each otheragent pools that were approximately the same average performance (e.g.,quality).

An average difference of 0 does not necessarily imply that both pairingstrategies are balanced (e.g., average performance of available agentsof approximately 50). For example, if the first pairing strategy isPBR_A with an average available agent performance of 25, and the secondpairing strategy is PBR_B with an average available agent performance of25, the difference will still be 0. From a benchmarking perspective, itmay acceptable for both pairing strategies to be unbalanced if theextent to which each is unbalanced is approximately the same. In thisway, each pairing strategy leaves an agent pool approximately as badlyas it found it, and neither pairing strategy is polluting the other.

FIG. 7 shows a schematic representation of an agent transition chart 700according to embodiments of the present disclosure. Agent transitioncharge 700 shows another example of a front-half/back-half comparison.At x=0 (e.g., Day 1), the difference between the average performance ofavailable agents transitioning into a first pairing strategy and out ofthe first pairing strategy over the course of the day was 25. At x=1,the difference was slightly above 25, and at x=3 the difference wasslightly below 25, but the overall differences over the course of a weekstayed close to 25. Conceptually, one of the pairing strategies isconsistently and significantly polluting the agent pools of anotherpairing strategy during at transitions. For example, if the front-halfof a PBR strategy is consistently receiving an agent pool with averageperformance of 50, and the back-half of the PBR strategy is consistentlyproviding an agent pool with average performance of only 25, thedifference is 25 on average.

An average difference significantly above 25 does not necessarily implythat either of the pairing strategies is balanced (e.g., averageperformance of available agents of approximately 50). For example, ifthe first pairing strategy is PBR_A with an average available agentperformance of 25, and the second pairing strategy is PBR_B with anaverage available agent performance of 0, the difference will still be25. The PBR_B pairing strategy is still polluting the benchmark, causingPBR_A to perform worse than it would in the absence of cycling withPBR_B, and causing PBR_B to perform better than it would in the absenceof cycling with PBR_A.

FIG. 8 shows a flow diagram of a benchmarking transition managementmethod 800 according to embodiments of the present disclosure. At block810, benchmarking transition management method 800 may begin. A contactcenter system may be cycling among at least two pairing strategies. Forexample, the contact center system may be switching between BP and PBRpairing strategies. At each transition from BP to PBR and vice versa,the agents available at each transition may be determined.

At block 810, a first average performance of available agents attransitions from the first pairing strategy (e.g., BP) to the secondpairing strategy (e.g., PBR) over time may be determined, based ondeterminations of available agents and their relative or otherwisenormalized performance for each transition. The first averageperformance may also be considered the “front-half” measurement of thesecond pairing strategy for the time period.

At block 820, in some embodiments, a second average performance ofavailable agents at transitions from the second pairing strategy (e.g.,PBR) to the first pairing strategy (e.g., BP) over time may bedetermined, based on determinations of available agents and theirrelative or otherwise normalized performance for each transition. Thesecond average performance may also be considered the “back-half”measurement of the second pairing strategy for the time period.

At block 830, in some embodiments, an average performance differencebetween the first and second average performance may be determined. Ifthe difference equals or approximates zero, it may be determined thatthere is no significant difference between the average performance ofavailable agents received from or provided to the first pairing strategyduring the measured time period. If the difference is greater than zero,it may be determined that the average performance of available agentsprovided by the first pairing strategy (e.g., BP) is higher than theaverage performance of available agents provided by the second pairingstrategy (e.g., PBR), indicating that the second pairing strategy may bepolluting the available agent pool and the benchmark.

At block 840, in some embodiments, a transition management report may begenerated. In some embodiments, the transition management report mayinclude the first average performance difference determined at block810, the second average performance difference determined at block 820,the average performance difference determined at block 840, or anycombination thereof. The data may be presented in a variety of formats,including but not limited to agent transition tables (e.g., agenttransition tables 200 and 300 (FIGS. 2 and 3)) or agent transitioncharts (e.g., agent transition charts 400, 500, 600, and 700 (FIGS.4-7)). The report may be dynamically generated and continuously orperiodically updated. The report may include user interface elements fordisplaying, sorting, filtering, or otherwise selecting which data todisplay and how to display it. The report may be fully auditable,enabling viewers to inspect the source data for each element. Forexample, the report interface may include user interface elements thatshow a list of agent identifiers available at a given transition andtheir corresponding relative or normalized performance measures.

At block 850, in some embodiments, at least one parameter of the firstor second pairing strategy may be adjusted to, for example, reduce theaverage performance difference determined at block 830. Reducing oreliminating a non-zero average performance difference may reduce oreliminate the extent to which one pairing strategy suppresses theperformance or pollutes the benchmark of a second pairing strategy.

For example, in a contact center system cycling between PBR and BP, PBRis likely to suppress a configuration of BP that targets a uniformutilization of agents. A variety of techniques allow for BP to target anon-uniform utilization of agents. For example, adjusting a “Kappa”parameter may bias BP toward PBR with respect to agent utilization.Kappa is described in, e.g., U.S. patent application Ser. No.14/956,086, which is incorporated by reference herein.

If Kappa is sufficiently high, it may be possible to eliminate benchmarksuppression or pollution (e.g., an average performance difference ofzero). However, in some environments, a high Kappa value may reduceoverall BP performance. In these situations, it may be desirable tocompensate for PBR benchmark pollution with have a high initial Kappavalue following a transition from PBR to BP, and reduce or eliminate theKappa adjustment (e.g., Kappa reduction from 1.5 to 1.0) over the courseof the first 3 minutes, 10 minutes, etc. The rate of such a “Kappa fade”may be adjusted to balance benchmark suppression from PBR with overallperformance at the front-half of a BP cycle.

Similarly, it may be desirable to have a high Kappa value prior to atransition from BP to PBR, producing or increasing a Kappa adjustment(e.g., Kappa increase from 1.0 to 1.5) over the course of the last 3minutes, 10 minutes, etc. The rate of such a “reverse Kappa fade” may beadjusted to balance benchmark suppression from PBR with overallperformance at the back-half of a BP cycle.

In contact center systems that cycle between FIFO and BP, the averageperformance difference may normally be zero, as both FIFO and BP targetbalanced agent utilization. However, in some environments, it may bedesirable or optimal for BP to target an unbalanced agent utilization(e.g., Kappa value greater than 1.0). If BP targets an unbalanced agentutilization, the average performance difference as compared to FIFO maybe non-zero, indicating a suppressed or polluted benchmark. In thesesituations, it may be desirable to reduce or eliminate a Kappaadjustment (e.g., Kappa decrease from 1.5 to 1.0) over the course of thelast 3 minutes, 10 minutes, etc. The rate of such a “Kappa fade” may beadjusted to reduce the average performance difference between BP andFIFO back to zero while balancing the optimization of overall BPperformance.

Following block 850, benchmarking transition management method 800 mayend. In some embodiments, benchmarking transition management method 800may return to block 810. In some embodiments, various steps may beoptional, performed in a different order, or performed in parallel withother steps. For example, the adjustment of at least one parameter atblock 850 may be optional, or it may be performed prior to, orsimultaneously with, the generation of a transition management report atblock 840.

At this point it should be noted that benchmarking performance in acontact center system in accordance with the present disclosure asdescribed above may involve the processing of input data and thegeneration of output data to some extent. This input data processing andoutput data generation may be implemented in hardware or software. Forexample, specific electronic components may be employed in a transitionmanagement module or similar or related circuitry for implementing thefunctions associated with benchmarking performance in a contact centersystem in accordance with the present disclosure as described above.Alternatively, one or more processors operating in accordance withinstructions may implement the functions associated with benchmarkingperformance in a contact center system in accordance with the presentdisclosure as described above. If such is the case, it is within thescope of the present disclosure that such instructions may be stored onone or more non-transitory processor readable storage media (e.g., amagnetic disk or other storage medium), or transmitted to one or moreprocessors via one or more signals embodied in one or more carrierwaves.

The present disclosure is not to be limited in scope by the specificembodiments described herein. Indeed, other various embodiments of andmodifications to the present disclosure, in addition to those describedherein, will be apparent to those of ordinary skill in the art from theforegoing description and accompanying drawings. Thus, such otherembodiments and modifications are intended to fall within the scope ofthe present disclosure. Further, although the present disclosure hasbeen described herein in the context of at least one particularimplementation in at least one particular environment for at least oneparticular purpose, those of ordinary skill in the art will recognizethat its usefulness is not limited thereto and that the presentdisclosure may be beneficially implemented in any number of environmentsfor any number of purposes. Accordingly, the claims set forth belowshould be construed in view of the full breadth and spirit of thepresent disclosure as described herein.

The invention claimed is:
 1. A method comprising: receiving, by at leastone computer processor communicatively coupled to and configured tooperate in a contact center system, a first pairing strategy and asecond pairing strategy; pairing, in a switch of the contact centersystem, a first plurality of contact-agent interactions in the contactcenter system using the first pairing strategy and a second plurality ofcontact-agent interactions using the second pairing strategy;determining, by the at least one computer processor, a first pluralityof agents available at a transition from the first pairing strategy tothe second pairing strategy; and outputting, by the at least onecomputer processor, an impact on performance of the second pairingstrategy based on the determining.
 2. The method of claim 1, wherein thepairing further comprises cycling between the first and second pairingstrategies periodically.
 3. The method of claim 2, wherein the contactcenter cycles between the first and second pairing strategies based onfactors other than time.
 4. The method of claim 1, further comprising:determining, by the at least one computer processor, a first performancemeasurement of the first plurality of agents, wherein the impact onperformance of the second pairing strategy is further based on the firstperformance measurement of the first plurality of agents.
 5. The methodof claim 4, wherein the first performance measurement of the firstplurality of agents is an average performance.
 6. The method of claim 1,further comprising: generating, by the at least one computer processor,a report for display on a graphical user interface based on theoutputting.
 7. The method of claim 4, further comprising: determining,by the at least one computer processor, a second plurality of agentsavailable before the pairing of the first plurality of contact-agentinteractions in the contact center system using the first pairingstrategy; determining, by the at least one computer processor, a secondperformance measurement of the second plurality of agents; andcomparing, by the at least one computer processor, the first performancemeasurement to the second performance measurement; wherein the impact onperformance of the second pairing strategy is further based on comparingthe first performance measurement to the second performance measurement.8. A system comprising: at least one computer processor communicativelycoupled to and configured to operate in a contact center system, whereinthe at least one computer processor is further configured to: receive afirst pairing strategy and a second pairing strategy; pair, in a switchof the contact center system, a first plurality of contact-agentinteractions in the contact center system using the first pairingstrategy and a second plurality of contact-agent interactions using thesecond pairing strategy; determine a first plurality of agents availableat a transition from the first pairing strategy to the second pairingstrategy; and output an impact on performance of the second pairingstrategy based on the determining.
 9. The system of claim 8, wherein thepairing further comprises cycling between the first and second pairingstrategies periodically.
 10. The system of claim 9, wherein the contactcenter cycles between the first and second pairing strategies based onfactors other than time.
 11. The system of claim 8, wherein the at leastone computer processor is further configured to: determine a firstperformance measurement of the first plurality of agents, wherein theimpact on performance of the second pairing strategy is further based onthe first performance measurement of the first plurality of agents. 12.The system of claim 11, wherein the first performance measurement of thefirst plurality of agents is an average performance.
 13. The system ofclaim 8, wherein the at least one computer processor is furtherconfigured to: generate a report for display on a graphical userinterface based on the outputting.
 14. The system of claim 11, whereinthe at least one computer processor is further configured to: determinea second plurality of agents available before the pairing of the firstplurality of contact-agent interactions in the contact center systemusing the first pairing strategy; determine a second performancemeasurement of the second plurality of agents; and compare the firstperformance measurement to the second performance measurement; whereinthe impact on performance of the second pairing strategy is furtherbased on comparing the first performance measurement to the secondperformance measurement.
 15. An article of manufacture comprising: anon-transitory computer processor readable medium; and instructionsstored on the medium; wherein the instructions are configured to bereadable from the medium by at least one computer processorcommunicatively coupled to and configured to operate in a contact centersystem and thereby cause the at least one computer processor to operateso as to: receive a first pairing strategy and a second pairingstrategy; pair, in a switch of the contact center system, a firstplurality of contact-agent interactions in the contact center systemusing the first pairing strategy and a second plurality of contact-agentinteractions using the second pairing strategy; determine a firstplurality of agents available at a transition from the first pairingstrategy to the second pairing strategy; and output an impact onperformance of the second pairing strategy based on the determining. 16.The article of manufacture of claim 15, wherein the pairing furthercomprises cycling between the first and second pairing strategiesperiodically.
 17. The article of manufacture of claim 16, wherein thecontact center cycles between the first and second pairing strategiesbased on factors other than time.
 18. The article of manufacture ofclaim 15, wherein the instructions further cause the at least onecomputer processor to operate so as to: determine a first performancemeasurement of the first plurality of agents, wherein the impact onperformance of the second pairing strategy is further based on the firstperformance measurement of the first plurality of agents.
 19. Thearticle of manufacture of claim 18, wherein the first performancemeasurement of the first plurality of agents is an average performance.20. The article of manufacture of claim 15, wherein the instructionsfurther cause the at least one computer processor to operate so as to:generate a report for display on a graphical user interface based on theoutputting.
 21. The article of manufacture of claim 18, wherein theinstructions further cause the at least one computer processor tooperate so as to: determine a second plurality of agents availablebefore the pairing of the first plurality of contact-agent interactionsin the contact center system using the first pairing strategy; determinea second performance measurement of the second plurality of agents; andcompare the first performance measurement to the second performancemeasurement; wherein the impact on performance of the second pairingstrategy is further based on comparing the first performance measurementto the second performance measurement.